In fingerprint recognition, there are two classes of characteristic points: (1) high-level features which include 0 to a few deltas and 1 to 2 cores; (2) low-level features which include the ending points and the bifurcation points.
Since the ridge-flow orientation of a fingerprint at a feature point will be different from the orientation of other part of the image, it can be relied on to determine the high-level features of the fingerprint. In fact, when an expert is identifying a fingerprint, the first characteristics being observed are these two characteristic points of the high-level features. As such, these features cannot be ignored in the development of an automatic fingerprint recognition system.
Each fingerprint may have a different number of core points and deltas. Therefore determining the high-level feature points will help make initial classifications for the fingerprints. However, as a major difficulty to the automatic fingerprint recognition, the fingerprint image acquired (for the same finger) may be different from each input of the image. This is because during each fingerprint acquisition, a person may either press his finger with different strength or in a different orientation that his fingerprint may be distorted. Therefore to re-orientate the fingerprint image and identify its location, such as using the cluster of core points and deltas as the basis, to simplify the recognition process and to improve the rate of recognition has become a principal object in automatic fingerprint recognition.
However, reviewing the conventional known technique, it can only determine one core point (a dual whole fingerprint has two core points), and cannot determine any delta point. Besides, it only divides the fingerprint ridge flow into four directions after the processing, which is not precise and can not determine the core point location so precisely.
U.S. Pat. No. 5,140,642 to Hsu et al. disclosed a method to automatically find out the actual position of the core point of a finger print by using the characteristics of the ridge flow of fingerprint. However, it also does not disclose a method to determine the delta points, thereby still being unsatisfactory for a precise recognition of fingerprints.